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Bayesian belief network model to predict human-wildlife conflict in protected areas
Santiago García-Lloré1, Richard C Stedman2, Angela K Fuller3
1New York Cooperative Fish and Wildlife Research Unit, Ashley School of Global Development and the Environment, Cornell University, Ithaca, NY, 14853, USA. sag337@cornell.edu.
Scientific Reports
|June 19, 2026
Summary
Human-wildlife conflict (HWC) is a major global issue. A Bayesian Belief Network (BBN) model effectively predicted HWC risk, showing governance and wildlife acceptance are key to reducing conflict.
Area of Science:
- Conservation Science
- Ecology
- Environmental Management
Background:
- Human-wildlife conflict (HWC) presents a significant global challenge, impacting both human livelihoods and biodiversity conservation.
- Effective prediction and mitigation strategies are crucial for managing HWC in protected areas.
Purpose of the Study:
- To develop a large-scale predictive model for human-wildlife conflict (HWC) risk using a Bayesian Belief Network (BBN).
- To identify key drivers of HWC and assess potential mitigation strategies in Andean protected areas.
Main Methods:
- A survey of 1,011 park rangers across 135 terrestrial protected areas in three Andean countries.
- Development and application of a Bayesian Belief Network (BBN) model to analyze HWC incidents and drivers.
- Sensitivity analysis to evaluate the impact of different factors on HWC risk.
Main Results:
- Key drivers of HWC risk were identified as governance, wildlife acceptance, participation, and habitat quality.
- Enhancing governance and wildlife acceptance could potentially reduce HWC risk by over 85%.
- The BBN model proved scalable and effective in identifying risk-reduction strategies at various scales.
Conclusions:
- Strengthening governance, increasing wildlife acceptance, and promoting community participation are vital for mitigating HWC.
- Bayesian Belief Networks (BBNs) offer a flexible, cost-effective, and data-driven tool for wildlife managers to inform decision-making and promote coexistence.
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